Analysis on techniques used to recognize and identifying the Human emotions

Facial expression is a major area for non-verbal language in day to day life communication. As the statistical analysis shows only 7 percent of the message in communication was covered in verbal communication while 55 percent transmitted by facial expression. Emotional expression has been a research subject of physiology since Darwin’s work on emotional expression in the 19th century. According to Psychological theory the classification of human emotion is classified majorly into six emotions: happiness, fear, anger, surprise, disgust, and sadness. Facial expressions which involve the emotions and the nature of speech play a foremost role in expressing these emotions. Thereafter, researchers developed a system based on Anatomic of face named Facial Action Coding System (FACS) in 1970. Ever since the development of FACS there is a rapid progress of research in the domain of emotion recognition. This work is intended to give a thorough comparative analysis of the various techniques and methods that were applied to recognize and identify human emotions. This analysis results will help to identify the proper and suitable techniques, algorithms and the methodologies for future research directions. In this paper extensive analysis on the various recognition techniques used to identify the complexity in recognizing the facial expression is presented. This work will also help researchers and scholars to ease out the problem in choosing the techniques used in the identification of the facial expression domain

A Review on Facial Expression Recognition Techniques

Facial expression is in the topic of active research over the past few decades. Recognition and extracting various emotions and validating those emotions from the facial expression become very important in human computer interaction. Interpreting such human expression remains and much of the research is required about the way they relate to human affect. Apart from H-I interfaces other applications include awareness system, medical diagnosis, surveillance, law enforcement, automated tutoring system and many more. In the recent year different technique have been put forward for developing automated facial expression recognition system. This paper present quick survey on some of the facial expression recognition techniques. A comparative study is carried out using various feature extraction techniques. We define taxonomy of the field and cover all the steps from face detection to facial expression classification

Automatic Generation of Facial Expression Using Triangular Geometric Deformation

AbstractThis paper presents an image deformation algorithm and constructs an automatic facial expression generation system to generate new facial expressions in neutral state. After the users input the face image in a neutral state into the system, the system separates the possible facial areas and the image background by skin color segmentation. It then uses the morphological operation to remove noise and to capture the organs of facial expression, such as the eyes, mouth, eyebrow, and nose. The feature control points are labeled according to the feature points (FPs) defined by MPEG-4. After the designation of the deformation expression, the system also increases the image correction points based on the obtained FP coordinates. The FPs are utilized as image deformation units by triangular segmentation. The triangle is split into two vectors. The triangle points are regarded as linear combinations of two vectors, and the coefficients of the linear combinations correspond to the triangular vectors of the original image. Next, the corresponding coordinates are obtained to complete the image correction by image interpolation technology to generate the new expression. As for the proposed deformation algorithm, 10 additional correction points are generated in the positions corresponding to the FPs obtained according to MPEG-4. Obtaining the correction points within a very short operation time is easy. Using a particular triangulation for deformation can extend the material area without narrowing the unwanted material area, thus saving the filling material operation in some areas